Overview

Dataset statistics

Number of variables21
Number of observations9551
Missing cells9
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 MiB
Average record size in memory168.0 B

Variable types

Numeric7
Text6
Categorical4
Boolean4

Alerts

Switch to order menu has constant value "False"Constant
Aggregate rating is highly overall correlated with Rating color and 2 other fieldsHigh correlation
Country Code is highly overall correlated with CurrencyHigh correlation
Currency is highly overall correlated with Country Code and 2 other fieldsHigh correlation
Has Table booking is highly overall correlated with Price rangeHigh correlation
Latitude is highly overall correlated with CurrencyHigh correlation
Longitude is highly overall correlated with CurrencyHigh correlation
Price range is highly overall correlated with Has Table bookingHigh correlation
Rating color is highly overall correlated with Aggregate rating and 1 other fieldsHigh correlation
Rating text is highly overall correlated with Aggregate rating and 1 other fieldsHigh correlation
Votes is highly overall correlated with Aggregate ratingHigh correlation
Currency is highly imbalanced (81.0%)Imbalance
Is delivering now is highly imbalanced (96.6%)Imbalance
Average Cost for two is highly skewed (γ1 = 35.4779149)Skewed
Restaurant ID has unique valuesUnique
Longitude has 498 (5.2%) zerosZeros
Latitude has 498 (5.2%) zerosZeros
Aggregate rating has 2148 (22.5%) zerosZeros
Votes has 1094 (11.5%) zerosZeros

Reproduction

Analysis started2026-02-13 14:32:49.494591
Analysis finished2026-02-13 14:32:55.506544
Duration6.01 seconds
Software versionydata-profiling vv4.18.1
Download configurationconfig.json

Variables

Restaurant ID
Real number (ℝ)

Unique 

Distinct9551
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9051128.3
Minimum53
Maximum18500652
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size74.7 KiB
2026-02-13T20:02:55.588751image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum53
5-th percentile2199.5
Q1301962.5
median6004089
Q318352292
95-th percentile18458642
Maximum18500652
Range18500599
Interquartile range (IQR)18050329

Descriptive statistics

Standard deviation8791521.3
Coefficient of variation (CV)0.97131771
Kurtosis-1.9509964
Mean9051128.3
Median Absolute Deviation (MAD)6003111
Skewness0.061569976
Sum8.6447327 × 1010
Variance7.7290846 × 1013
MonotonicityNot monotonic
2026-02-13T20:02:55.709960image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
63176371
 
< 0.1%
182545201
 
< 0.1%
184625891
 
< 0.1%
183364741
 
< 0.1%
183364771
 
< 0.1%
183820471
 
< 0.1%
184415661
 
< 0.1%
184416691
 
< 0.1%
183963581
 
< 0.1%
62481
 
< 0.1%
Other values (9541)9541
99.9%
ValueCountFrequency (%)
531
< 0.1%
551
< 0.1%
601
< 0.1%
641
< 0.1%
651
< 0.1%
661
< 0.1%
671
< 0.1%
691
< 0.1%
731
< 0.1%
891
< 0.1%
ValueCountFrequency (%)
185006521
< 0.1%
185006391
< 0.1%
185006281
< 0.1%
185006181
< 0.1%
184994931
< 0.1%
184994821
< 0.1%
184994751
< 0.1%
184994741
< 0.1%
184994721
< 0.1%
184994711
< 0.1%
Distinct7446
Distinct (%)78.0%
Missing0
Missing (%)0.0%
Memory size74.7 KiB
2026-02-13T20:02:55.922804image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length54
Median length46
Mean length15.166579
Min length2

Characters and Unicode

Total characters144856
Distinct characters110
Distinct categories15 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6712 ?
Unique (%)70.3%

Sample

1st rowLe Petit Souffle
2nd rowIzakaya Kikufuji
3rd rowHeat - Edsa Shangri-La
4th rowOoma
5th rowSambo Kojin
ValueCountFrequency (%)
931
 
3.8%
the780
 
3.2%
cafe615
 
2.5%
restaurant455
 
1.9%
food391
 
1.6%
corner294
 
1.2%
pizza240
 
1.0%
sweets232
 
0.9%
kitchen224
 
0.9%
bar208
 
0.8%
Other values (5989)20178
82.2%
2026-02-13T20:02:56.239480image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a15445
 
10.7%
15015
 
10.4%
e11821
 
8.2%
i8195
 
5.7%
r7362
 
5.1%
n7307
 
5.0%
o7285
 
5.0%
t5928
 
4.1%
s5882
 
4.1%
h5418
 
3.7%
Other values (100)55198
38.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter102845
71.0%
Uppercase Letter23983
 
16.6%
Space Separator15015
 
10.4%
Other Punctuation1784
 
1.2%
Dash Punctuation623
 
0.4%
Decimal Number449
 
0.3%
Other Symbol54
 
< 0.1%
Connector Punctuation38
 
< 0.1%
Control26
 
< 0.1%
Math Symbol17
 
< 0.1%
Other values (5)22
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a15445
15.0%
e11821
11.5%
i8195
 
8.0%
r7362
 
7.2%
n7307
 
7.1%
o7285
 
7.1%
t5928
 
5.8%
s5882
 
5.7%
h5418
 
5.3%
l4360
 
4.2%
Other values (24)23842
23.2%
Uppercase Letter
ValueCountFrequency (%)
C3395
14.2%
B2253
 
9.4%
S2193
 
9.1%
T1685
 
7.0%
P1450
 
6.0%
D1442
 
6.0%
R1294
 
5.4%
M1274
 
5.3%
F1208
 
5.0%
K1157
 
4.8%
Other values (21)6632
27.7%
Other Punctuation
ValueCountFrequency (%)
'1033
57.9%
&487
27.3%
.159
 
8.9%
!52
 
2.9%
,20
 
1.1%
@11
 
0.6%
#7
 
0.4%
:6
 
0.3%
/6
 
0.3%
"2
 
0.1%
Decimal Number
ValueCountFrequency (%)
281
18.0%
179
17.6%
459
13.1%
349
10.9%
645
10.0%
736
8.0%
933
7.3%
529
 
6.5%
021
 
4.7%
817
 
3.8%
Control
ValueCountFrequency (%)
Œ9
34.6%
7
26.9%
ƒ2
 
7.7%
†2
 
7.7%
2
 
7.7%
Š1
 
3.8%
Ÿ1
 
3.8%
ˆ1
 
3.8%
‡1
 
3.8%
Currency Symbol
ValueCountFrequency (%)
$3
50.0%
¢2
33.3%
£1
 
16.7%
Math Symbol
ValueCountFrequency (%)
±11
64.7%
+6
35.3%
Open Punctuation
ValueCountFrequency (%)
(5
83.3%
{1
 
16.7%
Close Punctuation
ValueCountFrequency (%)
)5
83.3%
}1
 
16.7%
Space Separator
ValueCountFrequency (%)
15015
100.0%
Dash Punctuation
ValueCountFrequency (%)
-623
100.0%
Other Symbol
ValueCountFrequency (%)
©54
100.0%
Connector Punctuation
ValueCountFrequency (%)
_38
100.0%
Final Punctuation
ValueCountFrequency (%)
»3
100.0%
Initial Punctuation
ValueCountFrequency (%)
«1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin126828
87.6%
Common18028
 
12.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a15445
 
12.2%
e11821
 
9.3%
i8195
 
6.5%
r7362
 
5.8%
n7307
 
5.8%
o7285
 
5.7%
t5928
 
4.7%
s5882
 
4.6%
h5418
 
4.3%
l4360
 
3.4%
Other values (55)47825
37.7%
Common
ValueCountFrequency (%)
15015
83.3%
'1033
 
5.7%
-623
 
3.5%
&487
 
2.7%
.159
 
0.9%
281
 
0.4%
179
 
0.4%
459
 
0.3%
©54
 
0.3%
!52
 
0.3%
Other values (35)386
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII144614
99.8%
None242
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a15445
 
10.7%
15015
 
10.4%
e11821
 
8.2%
i8195
 
5.7%
r7362
 
5.1%
n7307
 
5.1%
o7285
 
5.0%
t5928
 
4.1%
s5882
 
4.1%
h5418
 
3.7%
Other values (72)54956
38.0%
None
ValueCountFrequency (%)
í89
36.8%
©54
22.3%
Û17
 
7.0%
ô12
 
5.0%
±11
 
4.5%
Œ9
 
3.7%
7
 
2.9%
ç5
 
2.1%
ó5
 
2.1%
ä4
 
1.7%
Other values (18)29
 
12.0%

Country Code
Real number (ℝ)

High correlation 

Distinct15
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.365616
Minimum1
Maximum216
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size74.7 KiB
2026-02-13T20:02:56.332633image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile215
Maximum216
Range215
Interquartile range (IQR)0

Descriptive statistics

Standard deviation56.750546
Coefficient of variation (CV)3.0900431
Kurtosis7.3925784
Mean18.365616
Median Absolute Deviation (MAD)0
Skewness3.0439653
Sum175410
Variance3220.6244
MonotonicityNot monotonic
2026-02-13T20:02:56.406315image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
18652
90.6%
216434
 
4.5%
21580
 
0.8%
3060
 
0.6%
21460
 
0.6%
18960
 
0.6%
14840
 
0.4%
20834
 
0.4%
1424
 
0.3%
16222
 
0.2%
Other values (5)85
 
0.9%
ValueCountFrequency (%)
18652
90.6%
1424
 
0.3%
3060
 
0.6%
374
 
< 0.1%
9421
 
0.2%
14840
 
0.4%
16222
 
0.2%
16620
 
0.2%
18420
 
0.2%
18960
 
0.6%
ValueCountFrequency (%)
216434
4.5%
21580
 
0.8%
21460
 
0.6%
20834
 
0.4%
19120
 
0.2%
18960
 
0.6%
18420
 
0.2%
16620
 
0.2%
16222
 
0.2%
14840
 
0.4%

City
Text

Distinct141
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size74.7 KiB
2026-02-13T20:02:56.572952image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length22
Median length9
Mean length8.1586221
Min length3

Characters and Unicode

Total characters77923
Distinct characters57
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)0.5%

Sample

1st rowMakati City
2nd rowMakati City
3rd rowMandaluyong City
4th rowMandaluyong City
5th rowMandaluyong City
ValueCountFrequency (%)
new5473
35.7%
delhi5473
35.7%
gurgaon1118
 
7.3%
noida1080
 
7.0%
faridabad251
 
1.6%
city82
 
0.5%
ghaziabad25
 
0.2%
lucknow21
 
0.1%
bay21
 
0.1%
guwahati21
 
0.1%
Other values (155)1759
 
11.5%
2026-02-13T20:02:56.862166image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e11659
15.0%
i7587
9.7%
N6593
8.5%
h5997
 
7.7%
l5979
 
7.7%
5773
 
7.4%
D5634
 
7.2%
w5598
 
7.2%
a4948
 
6.3%
o3096
 
4.0%
Other values (47)15059
19.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter56770
72.9%
Uppercase Letter15319
 
19.7%
Space Separator5773
 
7.4%
Other Punctuation20
 
< 0.1%
Currency Symbol20
 
< 0.1%
Connector Punctuation20
 
< 0.1%
Dash Punctuation1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e11659
20.5%
i7587
13.4%
h5997
10.6%
l5979
10.5%
w5598
9.9%
a4948
8.7%
o3096
 
5.5%
r2126
 
3.7%
d2052
 
3.6%
n2016
 
3.6%
Other values (17)5712
10.1%
Uppercase Letter
ValueCountFrequency (%)
N6593
43.0%
D5634
36.8%
G1204
 
7.9%
F254
 
1.7%
C226
 
1.5%
A223
 
1.5%
P153
 
1.0%
B150
 
1.0%
S140
 
0.9%
M135
 
0.9%
Other values (15)607
 
4.0%
Space Separator
ValueCountFrequency (%)
5773
100.0%
Other Punctuation
ValueCountFrequency (%)
/20
100.0%
Currency Symbol
ValueCountFrequency (%)
£20
100.0%
Connector Punctuation
ValueCountFrequency (%)
_20
100.0%
Dash Punctuation
ValueCountFrequency (%)
-1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin72089
92.5%
Common5834
 
7.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e11659
16.2%
i7587
10.5%
N6593
9.1%
h5997
8.3%
l5979
8.3%
D5634
7.8%
w5598
7.8%
a4948
 
6.9%
o3096
 
4.3%
r2126
 
2.9%
Other values (42)12872
17.9%
Common
ValueCountFrequency (%)
5773
99.0%
/20
 
0.3%
£20
 
0.3%
_20
 
0.3%
-1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII77835
99.9%
None88
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e11659
15.0%
i7587
9.7%
N6593
8.5%
h5997
7.7%
l5979
 
7.7%
5773
 
7.4%
D5634
 
7.2%
w5598
 
7.2%
a4948
 
6.4%
o3096
 
4.0%
Other values (43)14971
19.2%
None
ValueCountFrequency (%)
í40
45.5%
£20
22.7%
Û14
 
15.9%
Á14
 
15.9%

Address
Text

Distinct8918
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Memory size74.7 KiB
2026-02-13T20:02:57.061943image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length132
Median length102
Mean length53.541828
Min length13

Characters and Unicode

Total characters511378
Distinct characters90
Distinct categories13 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8541 ?
Unique (%)89.4%

Sample

1st rowThird Floor, Century City Mall, Kalayaan Avenue, Poblacion, Makati City
2nd rowLittle Tokyo, 2277 Chino Roces Avenue, Legaspi Village, Makati City
3rd rowEdsa Shangri-La, 1 Garden Way, Ortigas, Mandaluyong City
4th rowThird Floor, Mega Fashion Hall, SM Megamall, Ortigas, Mandaluyong City
5th rowThird Floor, Mega Atrium, SM Megamall, Ortigas, Mandaluyong City
ValueCountFrequency (%)
new5737
 
6.9%
delhi5628
 
6.7%
sector2092
 
2.5%
road1956
 
2.3%
nagar1804
 
2.2%
market1734
 
2.1%
near1681
 
2.0%
floor1340
 
1.6%
gurgaon1165
 
1.4%
noida1146
 
1.4%
Other values (9054)59200
70.9%
2026-02-13T20:02:57.595011image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
74018
 
14.5%
a45036
 
8.8%
e33224
 
6.5%
,31658
 
6.2%
r26155
 
5.1%
o23614
 
4.6%
i22676
 
4.4%
l19476
 
3.8%
h16369
 
3.2%
n16158
 
3.2%
Other values (80)202994
39.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter293609
57.4%
Uppercase Letter79301
 
15.5%
Space Separator74018
 
14.5%
Other Punctuation33556
 
6.6%
Decimal Number27508
 
5.4%
Dash Punctuation2884
 
0.6%
Open Punctuation154
 
< 0.1%
Close Punctuation154
 
< 0.1%
Control67
 
< 0.1%
Connector Punctuation62
 
< 0.1%
Other values (3)65
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a45036
15.3%
e33224
11.3%
r26155
8.9%
o23614
 
8.0%
i22676
 
7.7%
l19476
 
6.6%
h16369
 
5.6%
n16158
 
5.5%
t15998
 
5.4%
d10270
 
3.5%
Other values (21)64633
22.0%
Uppercase Letter
ValueCountFrequency (%)
N11717
14.8%
D8344
10.5%
S7927
10.0%
M6408
 
8.1%
C5374
 
6.8%
G4940
 
6.2%
P4243
 
5.4%
A3971
 
5.0%
B3760
 
4.7%
R3416
 
4.3%
Other values (19)19201
24.2%
Decimal Number
ValueCountFrequency (%)
16551
23.8%
24191
15.2%
33419
12.4%
42355
 
8.6%
52324
 
8.4%
02157
 
7.8%
61855
 
6.7%
71686
 
6.1%
81629
 
5.9%
91341
 
4.9%
Other Punctuation
ValueCountFrequency (%)
,31658
94.3%
/1274
 
3.8%
.301
 
0.9%
&278
 
0.8%
'39
 
0.1%
#6
 
< 0.1%
Control
ValueCountFrequency (%)
35
52.2%
ˆ19
28.4%
6
 
9.0%
Œ6
 
9.0%
€1
 
1.5%
Currency Symbol
ValueCountFrequency (%)
£29
93.5%
¢2
 
6.5%
Space Separator
ValueCountFrequency (%)
74018
100.0%
Dash Punctuation
ValueCountFrequency (%)
-2884
100.0%
Open Punctuation
ValueCountFrequency (%)
(154
100.0%
Close Punctuation
ValueCountFrequency (%)
)154
100.0%
Connector Punctuation
ValueCountFrequency (%)
_62
100.0%
Math Symbol
ValueCountFrequency (%)
±26
100.0%
Other Symbol
ValueCountFrequency (%)
©8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin372910
72.9%
Common138468
 
27.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a45036
 
12.1%
e33224
 
8.9%
r26155
 
7.0%
o23614
 
6.3%
i22676
 
6.1%
l19476
 
5.2%
h16369
 
4.4%
n16158
 
4.3%
t15998
 
4.3%
N11717
 
3.1%
Other values (50)142487
38.2%
Common
ValueCountFrequency (%)
74018
53.5%
,31658
22.9%
16551
 
4.7%
24191
 
3.0%
33419
 
2.5%
-2884
 
2.1%
42355
 
1.7%
52324
 
1.7%
02157
 
1.6%
61855
 
1.3%
Other values (20)7056
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII510992
99.9%
None386
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
74018
 
14.5%
a45036
 
8.8%
e33224
 
6.5%
,31658
 
6.2%
r26155
 
5.1%
o23614
 
4.6%
i22676
 
4.4%
l19476
 
3.8%
h16369
 
3.2%
n16158
 
3.2%
Other values (64)202608
39.6%
None
ValueCountFrequency (%)
í132
34.2%
Û54
14.0%
ô43
 
11.1%
35
 
9.1%
£29
 
7.5%
±26
 
6.7%
ˆ19
 
4.9%
Á17
 
4.4%
©8
 
2.1%
Œ6
 
1.6%
Other values (6)17
 
4.4%
Distinct1208
Distinct (%)12.6%
Missing0
Missing (%)0.0%
Memory size74.7 KiB
2026-02-13T20:02:57.819479image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length51
Median length45
Mean length14.014868
Min length3

Characters and Unicode

Total characters133856
Distinct characters84
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique551 ?
Unique (%)5.8%

Sample

1st rowCentury City Mall, Poblacion, Makati City
2nd rowLittle Tokyo, Legaspi Village, Makati City
3rd rowEdsa Shangri-La, Ortigas, Mandaluyong City
4th rowSM Megamall, Ortigas, Mandaluyong City
5th rowSM Megamall, Ortigas, Mandaluyong City
ValueCountFrequency (%)
sector1627
 
7.2%
nagar1190
 
5.3%
vihar613
 
2.7%
mall588
 
2.6%
road488
 
2.2%
phase463
 
2.0%
dlf382
 
1.7%
1368
 
1.6%
place314
 
1.4%
colony266
 
1.2%
Other values (1390)16292
72.1%
2026-02-13T20:02:58.158442image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a17914
 
13.4%
13084
 
9.8%
r9236
 
6.9%
e7915
 
5.9%
i6287
 
4.7%
o6275
 
4.7%
t5667
 
4.2%
n5554
 
4.1%
l5109
 
3.8%
h4677
 
3.5%
Other values (74)52138
39.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter92730
69.3%
Uppercase Letter21770
 
16.3%
Space Separator13084
 
9.8%
Decimal Number4179
 
3.1%
Other Punctuation1684
 
1.3%
Close Punctuation140
 
0.1%
Open Punctuation140
 
0.1%
Dash Punctuation78
 
0.1%
Connector Punctuation24
 
< 0.1%
Control14
 
< 0.1%
Other values (2)13
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a17914
19.3%
r9236
10.0%
e7915
 
8.5%
i6287
 
6.8%
o6275
 
6.8%
t5667
 
6.1%
n5554
 
6.0%
l5109
 
5.5%
h4677
 
5.0%
u3025
 
3.3%
Other values (20)21071
22.7%
Uppercase Letter
ValueCountFrequency (%)
S3165
14.5%
P1946
 
8.9%
N1845
 
8.5%
M1789
 
8.2%
C1667
 
7.7%
G1359
 
6.2%
K1213
 
5.6%
V1141
 
5.2%
R992
 
4.6%
D922
 
4.2%
Other values (18)5731
26.3%
Decimal Number
ValueCountFrequency (%)
11136
27.2%
2772
18.5%
3566
13.5%
5386
 
9.2%
4334
 
8.0%
6250
 
6.0%
8236
 
5.6%
7218
 
5.2%
9141
 
3.4%
0140
 
3.4%
Other Punctuation
ValueCountFrequency (%)
,1638
97.3%
&18
 
1.1%
'10
 
0.6%
.10
 
0.6%
/6
 
0.4%
:2
 
0.1%
Control
ValueCountFrequency (%)
11
78.6%
ˆ3
 
21.4%
Currency Symbol
ValueCountFrequency (%)
£3
75.0%
¢1
 
25.0%
Space Separator
ValueCountFrequency (%)
13084
100.0%
Close Punctuation
ValueCountFrequency (%)
)140
100.0%
Open Punctuation
ValueCountFrequency (%)
(140
100.0%
Dash Punctuation
ValueCountFrequency (%)
-78
100.0%
Connector Punctuation
ValueCountFrequency (%)
_24
100.0%
Math Symbol
ValueCountFrequency (%)
±9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin114500
85.5%
Common19356
 
14.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a17914
15.6%
r9236
 
8.1%
e7915
 
6.9%
i6287
 
5.5%
o6275
 
5.5%
t5667
 
4.9%
n5554
 
4.9%
l5109
 
4.5%
h4677
 
4.1%
S3165
 
2.8%
Other values (48)42701
37.3%
Common
ValueCountFrequency (%)
13084
67.6%
,1638
 
8.5%
11136
 
5.9%
2772
 
4.0%
3566
 
2.9%
5386
 
2.0%
4334
 
1.7%
6250
 
1.3%
8236
 
1.2%
7218
 
1.1%
Other values (16)736
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII133764
99.9%
None92
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a17914
 
13.4%
13084
 
9.8%
r9236
 
6.9%
e7915
 
5.9%
i6287
 
4.7%
o6275
 
4.7%
t5667
 
4.2%
n5554
 
4.2%
l5109
 
3.8%
h4677
 
3.5%
Other values (63)52046
38.9%
None
ValueCountFrequency (%)
í40
43.5%
11
 
12.0%
Û10
 
10.9%
±9
 
9.8%
ô9
 
9.8%
£3
 
3.3%
ˆ3
 
3.3%
ì2
 
2.2%
Ç2
 
2.2%
ç2
 
2.2%
Distinct1265
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size74.7 KiB
2026-02-13T20:02:58.389239image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length64
Median length56
Mean length24.170139
Min length7

Characters and Unicode

Total characters230849
Distinct characters85
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique566 ?
Unique (%)5.9%

Sample

1st rowCentury City Mall, Poblacion, Makati City, Makati City
2nd rowLittle Tokyo, Legaspi Village, Makati City, Makati City
3rd rowEdsa Shangri-La, Ortigas, Mandaluyong City, Mandaluyong City
4th rowSM Megamall, Ortigas, Mandaluyong City, Mandaluyong City
5th rowSM Megamall, Ortigas, Mandaluyong City, Mandaluyong City
ValueCountFrequency (%)
new5580
 
14.7%
delhi5578
 
14.7%
sector1627
 
4.3%
noida1246
 
3.3%
gurgaon1202
 
3.2%
nagar1190
 
3.1%
vihar613
 
1.6%
mall588
 
1.6%
road488
 
1.3%
phase463
 
1.2%
Other values (1449)19343
51.0%
2026-02-13T20:02:58.749099image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28404
 
12.3%
a22862
 
9.9%
e19574
 
8.5%
i13874
 
6.0%
r11362
 
4.9%
,11185
 
4.8%
l11088
 
4.8%
h10674
 
4.6%
o9363
 
4.1%
N8438
 
3.7%
Other values (75)84025
36.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter149480
64.8%
Uppercase Letter37085
 
16.1%
Space Separator28404
 
12.3%
Other Punctuation11251
 
4.9%
Decimal Number4179
 
1.8%
Close Punctuation140
 
0.1%
Open Punctuation140
 
0.1%
Dash Punctuation79
 
< 0.1%
Connector Punctuation44
 
< 0.1%
Currency Symbol24
 
< 0.1%
Other values (2)23
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a22862
15.3%
e19574
13.1%
i13874
9.3%
r11362
 
7.6%
l11088
 
7.4%
h10674
 
7.1%
o9363
 
6.3%
n7562
 
5.1%
w6205
 
4.2%
t6159
 
4.1%
Other values (20)30757
20.6%
Uppercase Letter
ValueCountFrequency (%)
N8438
22.8%
D6556
17.7%
S3305
 
8.9%
G2563
 
6.9%
P2099
 
5.7%
M1924
 
5.2%
C1893
 
5.1%
K1274
 
3.4%
V1224
 
3.3%
R1075
 
2.9%
Other values (19)6734
18.2%
Decimal Number
ValueCountFrequency (%)
11136
27.2%
2772
18.5%
3566
13.5%
5386
 
9.2%
4334
 
8.0%
6250
 
6.0%
8236
 
5.6%
7218
 
5.2%
9141
 
3.4%
0140
 
3.4%
Other Punctuation
ValueCountFrequency (%)
,11185
99.4%
/26
 
0.2%
&18
 
0.2%
'10
 
0.1%
.10
 
0.1%
:2
 
< 0.1%
Currency Symbol
ValueCountFrequency (%)
£23
95.8%
¢1
 
4.2%
Control
ValueCountFrequency (%)
11
78.6%
ˆ3
 
21.4%
Space Separator
ValueCountFrequency (%)
28404
100.0%
Close Punctuation
ValueCountFrequency (%)
)140
100.0%
Open Punctuation
ValueCountFrequency (%)
(140
100.0%
Dash Punctuation
ValueCountFrequency (%)
-79
100.0%
Connector Punctuation
ValueCountFrequency (%)
_44
100.0%
Math Symbol
ValueCountFrequency (%)
±9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin186565
80.8%
Common44284
 
19.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a22862
 
12.3%
e19574
 
10.5%
i13874
 
7.4%
r11362
 
6.1%
l11088
 
5.9%
h10674
 
5.7%
o9363
 
5.0%
N8438
 
4.5%
n7562
 
4.1%
D6556
 
3.5%
Other values (49)65212
35.0%
Common
ValueCountFrequency (%)
28404
64.1%
,11185
 
25.3%
11136
 
2.6%
2772
 
1.7%
3566
 
1.3%
5386
 
0.9%
4334
 
0.8%
6250
 
0.6%
8236
 
0.5%
7218
 
0.5%
Other values (16)797
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII230669
99.9%
None180
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
28404
 
12.3%
a22862
 
9.9%
e19574
 
8.5%
i13874
 
6.0%
r11362
 
4.9%
,11185
 
4.8%
l11088
 
4.8%
h10674
 
4.6%
o9363
 
4.1%
N8438
 
3.7%
Other values (63)83845
36.3%
None
ValueCountFrequency (%)
í80
44.4%
Û24
 
13.3%
£23
 
12.8%
Á14
 
7.8%
11
 
6.1%
ô9
 
5.0%
±9
 
5.0%
ˆ3
 
1.7%
ì2
 
1.1%
Ç2
 
1.1%
Other values (2)3
 
1.7%

Longitude
Real number (ℝ)

High correlation  Zeros 

Distinct8120
Distinct (%)85.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64.126574
Minimum-157.94849
Maximum174.83209
Zeros498
Zeros (%)5.2%
Negative578
Negative (%)6.1%
Memory size74.7 KiB
2026-02-13T20:02:58.849019image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-157.94849
5-th percentile-44.979336
Q177.081343
median77.191964
Q377.282006
95-th percentile77.510935
Maximum174.83209
Range332.78058
Interquartile range (IQR)0.20066325

Descriptive statistics

Standard deviation41.467058
Coefficient of variation (CV)0.64664389
Kurtosis8.2165863
Mean64.126574
Median Absolute Deviation (MAD)0.10160718
Skewness-2.8073278
Sum612472.91
Variance1719.5169
MonotonicityNot monotonic
2026-02-13T20:02:58.949588image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0498
 
5.2%
77.353663419
 
0.2%
77.230411512
 
0.1%
77.088687910
 
0.1%
77.25142649
 
0.1%
77.35357379
 
0.1%
77.36483328
 
0.1%
77.22053147
 
0.1%
77.2181877
 
0.1%
77.20418246
 
0.1%
Other values (8110)8966
93.9%
ValueCountFrequency (%)
-157.9484861
< 0.1%
-157.8360311
< 0.1%
-157.8315381
< 0.1%
-157.83124761
< 0.1%
-157.8311761
< 0.1%
-157.8271961
< 0.1%
-157.8259791
< 0.1%
-157.8227161
< 0.1%
-157.8134321
< 0.1%
-156.6938211
< 0.1%
ValueCountFrequency (%)
174.83208931
< 0.1%
174.8103051
< 0.1%
174.7932571
< 0.1%
174.7850511
< 0.1%
174.7824271
< 0.1%
174.78066671
< 0.1%
174.7803451
< 0.1%
174.7794411
< 0.1%
174.77922371
< 0.1%
174.77916672
< 0.1%

Latitude
Real number (ℝ)

High correlation  Zeros 

Distinct8677
Distinct (%)90.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.854381
Minimum-41.330428
Maximum55.97698
Zeros498
Zeros (%)5.2%
Negative203
Negative (%)2.1%
Memory size74.7 KiB
2026-02-13T20:02:59.056076image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-41.330428
5-th percentile0
Q128.478713
median28.570469
Q328.642758
95-th percentile30.895511
Maximum55.97698
Range97.307408
Interquartile range (IQR)0.1640456

Descriptive statistics

Standard deviation11.007935
Coefficient of variation (CV)0.42576673
Kurtosis12.530803
Mean25.854381
Median Absolute Deviation (MAD)0.07656008
Skewness-3.0816354
Sum246935.19
Variance121.17464
MonotonicityNot monotonic
2026-02-13T20:02:59.156020image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0498
 
5.2%
28.574308616
 
0.2%
28.5514569
 
0.1%
28.57430019
 
0.1%
28.59710278
 
0.1%
28.6254457
 
0.1%
28.55034726
 
0.1%
28.569046
 
0.1%
28.556503475
 
0.1%
28.49520795
 
0.1%
Other values (8667)8982
94.0%
ValueCountFrequency (%)
-41.3304281
< 0.1%
-41.2961551
< 0.1%
-41.2961071
< 0.1%
-41.295971
< 0.1%
-41.294833331
< 0.1%
-41.2945651
< 0.1%
-41.2944021
< 0.1%
-41.2942341
< 0.1%
-41.2941541
< 0.1%
-41.293833331
< 0.1%
ValueCountFrequency (%)
55.976981
< 0.1%
55.9766441
< 0.1%
55.975097221
< 0.1%
55.964669441
< 0.1%
55.9570331
< 0.1%
55.954041
< 0.1%
55.953494441
< 0.1%
55.9522211
< 0.1%
55.9519741
< 0.1%
55.9496371
< 0.1%
Distinct1825
Distinct (%)19.1%
Missing9
Missing (%)0.1%
Memory size74.7 KiB
2026-02-13T20:02:59.367575image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length93
Median length77
Mean length19.924963
Min length3

Characters and Unicode

Total characters190124
Distinct characters52
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1278 ?
Unique (%)13.4%

Sample

1st rowFrench, Japanese, Desserts
2nd rowJapanese
3rd rowSeafood, Asian, Filipino, Indian
4th rowJapanese, Sushi
5th rowJapanese, Korean
ValueCountFrequency (%)
indian4682
16.9%
north3969
14.4%
food2855
 
10.3%
chinese2735
 
9.9%
fast1987
 
7.2%
mughlai995
 
3.6%
italian764
 
2.8%
bakery745
 
2.7%
continental736
 
2.7%
cafe707
 
2.6%
Other values (139)7480
27.0%
2026-02-13T20:02:59.709049image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18113
 
9.5%
n17601
 
9.3%
a16702
 
8.8%
e14520
 
7.6%
i13615
 
7.2%
t11839
 
6.2%
o11795
 
6.2%
,10168
 
5.3%
h9473
 
5.0%
r8647
 
4.5%
Other values (42)57651
30.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter134102
70.5%
Uppercase Letter27720
 
14.6%
Space Separator18113
 
9.5%
Other Punctuation10168
 
5.3%
Dash Punctuation19
 
< 0.1%
Connector Punctuation2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n17601
13.1%
a16702
12.5%
e14520
10.8%
i13615
10.2%
t11839
8.8%
o11795
8.8%
h9473
7.1%
r8647
6.4%
d8166
6.1%
s7950
5.9%
Other values (16)13794
10.3%
Uppercase Letter
ValueCountFrequency (%)
I5713
20.6%
F5002
18.0%
C4481
16.2%
N3988
14.4%
M1894
 
6.8%
S1729
 
6.2%
B1641
 
5.9%
A742
 
2.7%
D669
 
2.4%
P426
 
1.5%
Other values (12)1435
 
5.2%
Space Separator
ValueCountFrequency (%)
18113
100.0%
Other Punctuation
ValueCountFrequency (%)
,10168
100.0%
Dash Punctuation
ValueCountFrequency (%)
-19
100.0%
Connector Punctuation
ValueCountFrequency (%)
_2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin161822
85.1%
Common28302
 
14.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
n17601
10.9%
a16702
10.3%
e14520
 
9.0%
i13615
 
8.4%
t11839
 
7.3%
o11795
 
7.3%
h9473
 
5.9%
r8647
 
5.3%
d8166
 
5.0%
s7950
 
4.9%
Other values (38)41514
25.7%
Common
ValueCountFrequency (%)
18113
64.0%
,10168
35.9%
-19
 
0.1%
_2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII190122
> 99.9%
None2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18113
 
9.5%
n17601
 
9.3%
a16702
 
8.8%
e14520
 
7.6%
i13615
 
7.2%
t11839
 
6.2%
o11795
 
6.2%
,10168
 
5.3%
h9473
 
5.0%
r8647
 
4.5%
Other values (41)57649
30.3%
None
ValueCountFrequency (%)
í2
100.0%

Average Cost for two
Real number (ℝ)

Skewed 

Distinct140
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1199.2108
Minimum0
Maximum800000
Zeros18
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size74.7 KiB
2026-02-13T20:02:59.816429image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile40
Q1250
median400
Q3700
95-th percentile1700
Maximum800000
Range800000
Interquartile range (IQR)450

Descriptive statistics

Standard deviation16121.183
Coefficient of variation (CV)13.443161
Kurtosis1495.7774
Mean1199.2108
Median Absolute Deviation (MAD)200
Skewness35.477915
Sum11453662
Variance2.5989254 × 108
MonotonicityNot monotonic
2026-02-13T20:02:59.928927image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
500900
 
9.4%
300897
 
9.4%
400857
 
9.0%
200687
 
7.2%
600652
 
6.8%
250461
 
4.8%
350457
 
4.8%
700403
 
4.2%
150367
 
3.8%
100353
 
3.7%
Other values (130)3517
36.8%
ValueCountFrequency (%)
018
 
0.2%
74
 
< 0.1%
10128
1.3%
154
 
< 0.1%
2025
 
0.3%
25174
1.8%
3024
 
0.3%
3517
 
0.2%
40115
1.2%
4512
 
0.1%
ValueCountFrequency (%)
8000002
 
< 0.1%
5000001
 
< 0.1%
4500001
 
< 0.1%
3500001
 
< 0.1%
3000002
 
< 0.1%
2500002
 
< 0.1%
2000006
0.1%
1650001
 
< 0.1%
1500001
 
< 0.1%
1200001
 
< 0.1%

Currency
Categorical

High correlation  Imbalance 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size74.7 KiB
Indian Rupees(Rs.)
8652 
Dollar($)
 
482
Pounds(Σ)
 
80
Brazilian Real(R$)
 
60
Emirati Diram(AED)
 
60
Other values (7)
 
217

Length

Max length22
Median length18
Mean length17.385823
Min length7

Characters and Unicode

Total characters166052
Distinct characters38
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBotswana Pula(P)
2nd rowBotswana Pula(P)
3rd rowBotswana Pula(P)
4th rowBotswana Pula(P)
5th rowBotswana Pula(P)

Common Values

ValueCountFrequency (%)
Indian Rupees(Rs.)8652
90.6%
Dollar($)482
 
5.0%
Pounds(Σ)80
 
0.8%
Brazilian Real(R$)60
 
0.6%
Emirati Diram(AED)60
 
0.6%
Rand(R)60
 
0.6%
NewZealand($)40
 
0.4%
Turkish Lira(TL)34
 
0.4%
Botswana Pula(P)22
 
0.2%
Indonesian Rupiah(IDR)21
 
0.2%
Other values (2)40
 
0.4%

Length

2026-02-13T20:03:00.058321image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
indian8652
46.9%
rupees(rs8652
46.9%
dollar482
 
2.6%
pounds(Σ80
 
0.4%
brazilian60
 
0.3%
real(r60
 
0.3%
emirati60
 
0.3%
diram(aed60
 
0.3%
rand(r60
 
0.3%
newzealand40
 
0.2%
Other values (11)254
 
1.4%

Most occurring characters

ValueCountFrequency (%)
n17669
10.6%
R17666
10.6%
e17505
10.5%
s17461
10.5%
a9816
 
5.9%
(9551
 
5.8%
)9551
 
5.8%
i9122
 
5.5%
8909
 
5.4%
d8853
 
5.3%
Other values (28)39949
24.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter100942
60.8%
Uppercase Letter27705
 
16.7%
Open Punctuation9551
 
5.8%
Close Punctuation9551
 
5.8%
Space Separator8909
 
5.4%
Other Punctuation8652
 
5.2%
Currency Symbol662
 
0.4%
Control80
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n17669
17.5%
e17505
17.3%
s17461
17.3%
a9816
9.7%
i9122
9.0%
d8853
8.8%
u8829
8.7%
p8693
8.6%
l1166
 
1.2%
r770
 
0.8%
Other values (7)1058
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
R17666
63.8%
I8694
31.4%
D623
 
2.2%
P124
 
0.4%
E120
 
0.4%
L108
 
0.4%
B82
 
0.3%
T68
 
0.2%
A60
 
0.2%
N40
 
0.1%
Other values (4)120
 
0.4%
Currency Symbol
ValueCountFrequency (%)
$582
87.9%
£80
 
12.1%
Open Punctuation
ValueCountFrequency (%)
(9551
100.0%
Close Punctuation
ValueCountFrequency (%)
)9551
100.0%
Space Separator
ValueCountFrequency (%)
8909
100.0%
Other Punctuation
ValueCountFrequency (%)
.8652
100.0%
Control
ValueCountFrequency (%)
Œ80
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin128647
77.5%
Common37405
 
22.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
n17669
13.7%
R17666
13.7%
e17505
13.6%
s17461
13.6%
a9816
7.6%
i9122
7.1%
d8853
6.9%
u8829
6.9%
I8694
6.8%
p8693
6.8%
Other values (21)4339
 
3.4%
Common
ValueCountFrequency (%)
(9551
25.5%
)9551
25.5%
8909
23.8%
.8652
23.1%
$582
 
1.6%
Œ80
 
0.2%
£80
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII165892
99.9%
None160
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n17669
10.7%
R17666
10.6%
e17505
10.6%
s17461
10.5%
a9816
 
5.9%
(9551
 
5.8%
)9551
 
5.8%
i9122
 
5.5%
8909
 
5.4%
d8853
 
5.3%
Other values (26)39789
24.0%
None
ValueCountFrequency (%)
Œ80
50.0%
£80
50.0%

Has Table booking
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.5 KiB
False
8393 
True
1158 
ValueCountFrequency (%)
False8393
87.9%
True1158
 
12.1%
2026-02-13T20:03:00.139196image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.5 KiB
False
7100 
True
2451 
ValueCountFrequency (%)
False7100
74.3%
True2451
 
25.7%
2026-02-13T20:03:00.211495image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Is delivering now
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.5 KiB
False
9517 
True
 
34
ValueCountFrequency (%)
False9517
99.6%
True34
 
0.4%
2026-02-13T20:03:00.277950image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Switch to order menu
Boolean

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.5 KiB
False
9551 
ValueCountFrequency (%)
False9551
100.0%
2026-02-13T20:03:00.344409image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Price range
Categorical

High correlation 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size74.7 KiB
1
4444 
2
3113 
3
1408 
4
586 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters9551
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row4
4th row4
5th row4

Common Values

ValueCountFrequency (%)
14444
46.5%
23113
32.6%
31408
 
14.7%
4586
 
6.1%

Length

2026-02-13T20:03:00.434526image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-02-13T20:03:00.526898image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
14444
46.5%
23113
32.6%
31408
 
14.7%
4586
 
6.1%

Most occurring characters

ValueCountFrequency (%)
14444
46.5%
23113
32.6%
31408
 
14.7%
4586
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number9551
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
14444
46.5%
23113
32.6%
31408
 
14.7%
4586
 
6.1%

Most occurring scripts

ValueCountFrequency (%)
Common9551
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
14444
46.5%
23113
32.6%
31408
 
14.7%
4586
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII9551
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14444
46.5%
23113
32.6%
31408
 
14.7%
4586
 
6.1%

Aggregate rating
Real number (ℝ)

High correlation  Zeros 

Distinct33
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.66637
Minimum0
Maximum4.9
Zeros2148
Zeros (%)22.5%
Negative0
Negative (%)0.0%
Memory size74.7 KiB
2026-02-13T20:03:00.612178image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.5
median3.2
Q33.7
95-th percentile4.3
Maximum4.9
Range4.9
Interquartile range (IQR)1.2

Descriptive statistics

Standard deviation1.5163775
Coefficient of variation (CV)0.56870484
Kurtosis-0.58221714
Mean2.66637
Median Absolute Deviation (MAD)0.5
Skewness-0.95413047
Sum25466.5
Variance2.2994008
MonotonicityNot monotonic
2026-02-13T20:03:00.708050image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
02148
22.5%
3.2522
 
5.5%
3.1519
 
5.4%
3.4498
 
5.2%
3.3483
 
5.1%
3.5480
 
5.0%
3468
 
4.9%
3.6458
 
4.8%
3.7427
 
4.5%
3.8400
 
4.2%
Other values (23)3148
33.0%
ValueCountFrequency (%)
02148
22.5%
1.81
 
< 0.1%
1.92
 
< 0.1%
27
 
0.1%
2.115
 
0.2%
2.227
 
0.3%
2.347
 
0.5%
2.487
 
0.9%
2.5110
 
1.2%
2.6191
 
2.0%
ValueCountFrequency (%)
4.961
 
0.6%
4.825
 
0.3%
4.742
 
0.4%
4.678
 
0.8%
4.595
 
1.0%
4.4144
1.5%
4.3174
1.8%
4.2221
2.3%
4.1274
2.9%
4266
2.8%

Rating color
Categorical

High correlation 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size74.7 KiB
Orange
3737 
White
2148 
Yellow
2100 
Green
1079 
Dark Green
 
301

Length

Max length10
Median length6
Mean length5.7297665
Min length3

Characters and Unicode

Total characters54725
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDark Green
2nd rowDark Green
3rd rowGreen
4th rowDark Green
5th rowDark Green

Common Values

ValueCountFrequency (%)
Orange3737
39.1%
White2148
22.5%
Yellow2100
22.0%
Green1079
 
11.3%
Dark Green301
 
3.2%
Red186
 
1.9%

Length

2026-02-13T20:03:00.812132image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-02-13T20:03:00.901540image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
orange3737
37.9%
white2148
21.8%
yellow2100
21.3%
green1380
 
14.0%
dark301
 
3.1%
red186
 
1.9%

Most occurring characters

ValueCountFrequency (%)
e10931
20.0%
r5418
9.9%
n5117
9.4%
l4200
 
7.7%
a4038
 
7.4%
O3737
 
6.8%
g3737
 
6.8%
W2148
 
3.9%
h2148
 
3.9%
i2148
 
3.9%
Other values (10)11103
20.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter44572
81.4%
Uppercase Letter9852
 
18.0%
Space Separator301
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e10931
24.5%
r5418
12.2%
n5117
11.5%
l4200
 
9.4%
a4038
 
9.1%
g3737
 
8.4%
h2148
 
4.8%
i2148
 
4.8%
t2148
 
4.8%
w2100
 
4.7%
Other values (3)2587
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
O3737
37.9%
W2148
21.8%
Y2100
21.3%
G1380
 
14.0%
D301
 
3.1%
R186
 
1.9%
Space Separator
ValueCountFrequency (%)
301
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin54424
99.4%
Common301
 
0.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e10931
20.1%
r5418
10.0%
n5117
9.4%
l4200
 
7.7%
a4038
 
7.4%
O3737
 
6.9%
g3737
 
6.9%
W2148
 
3.9%
h2148
 
3.9%
i2148
 
3.9%
Other values (9)10802
19.8%
Common
ValueCountFrequency (%)
301
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII54725
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e10931
20.0%
r5418
9.9%
n5117
9.4%
l4200
 
7.7%
a4038
 
7.4%
O3737
 
6.8%
g3737
 
6.8%
W2148
 
3.9%
h2148
 
3.9%
i2148
 
3.9%
Other values (10)11103
20.3%

Rating text
Categorical

High correlation 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size74.7 KiB
Average
3737 
Not rated
2148 
Good
2100 
Very Good
1079 
Excellent
 
301

Length

Max length9
Median length7
Mean length7.0207308
Min length4

Characters and Unicode

Total characters67055
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowExcellent
2nd rowExcellent
3rd rowVery Good
4th rowExcellent
5th rowExcellent

Common Values

ValueCountFrequency (%)
Average3737
39.1%
Not rated2148
22.5%
Good2100
22.0%
Very Good1079
 
11.3%
Excellent301
 
3.2%
Poor186
 
1.9%

Length

2026-02-13T20:03:01.006063image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-02-13T20:03:01.125165image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
average3737
29.2%
good3179
24.9%
not2148
16.8%
rated2148
16.8%
very1079
 
8.4%
excellent301
 
2.4%
poor186
 
1.5%

Most occurring characters

ValueCountFrequency (%)
e11303
16.9%
o8878
13.2%
r7150
10.7%
a5885
8.8%
d5327
7.9%
t4597
6.9%
v3737
 
5.6%
A3737
 
5.6%
g3737
 
5.6%
3227
 
4.8%
Other values (10)9477
14.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter53198
79.3%
Uppercase Letter10630
 
15.9%
Space Separator3227
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e11303
21.2%
o8878
16.7%
r7150
13.4%
a5885
11.1%
d5327
10.0%
t4597
8.6%
v3737
 
7.0%
g3737
 
7.0%
y1079
 
2.0%
l602
 
1.1%
Other values (3)903
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
A3737
35.2%
G3179
29.9%
N2148
20.2%
V1079
 
10.2%
E301
 
2.8%
P186
 
1.7%
Space Separator
ValueCountFrequency (%)
3227
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin63828
95.2%
Common3227
 
4.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e11303
17.7%
o8878
13.9%
r7150
11.2%
a5885
9.2%
d5327
8.3%
t4597
7.2%
v3737
 
5.9%
A3737
 
5.9%
g3737
 
5.9%
G3179
 
5.0%
Other values (9)6298
9.9%
Common
ValueCountFrequency (%)
3227
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII67055
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e11303
16.9%
o8878
13.2%
r7150
10.7%
a5885
8.8%
d5327
7.9%
t4597
6.9%
v3737
 
5.6%
A3737
 
5.6%
g3737
 
5.6%
3227
 
4.8%
Other values (10)9477
14.1%

Votes
Real number (ℝ)

High correlation  Zeros 

Distinct1012
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean156.90975
Minimum0
Maximum10934
Zeros1094
Zeros (%)11.5%
Negative0
Negative (%)0.0%
Memory size74.7 KiB
2026-02-13T20:03:01.238992image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median31
Q3131
95-th percentile699
Maximum10934
Range10934
Interquartile range (IQR)126

Descriptive statistics

Standard deviation430.16915
Coefficient of variation (CV)2.7415068
Kurtosis128.22597
Mean156.90975
Median Absolute Deviation (MAD)30
Skewness8.8076367
Sum1498645
Variance185045.49
MonotonicityNot monotonic
2026-02-13T20:03:01.348958image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
01094
 
11.5%
1483
 
5.1%
2327
 
3.4%
3244
 
2.6%
4207
 
2.2%
7168
 
1.8%
5164
 
1.7%
6154
 
1.6%
10135
 
1.4%
8134
 
1.4%
Other values (1002)6441
67.4%
ValueCountFrequency (%)
01094
11.5%
1483
5.1%
2327
 
3.4%
3244
 
2.6%
4207
 
2.2%
5164
 
1.7%
6154
 
1.6%
7168
 
1.8%
8134
 
1.4%
9113
 
1.2%
ValueCountFrequency (%)
109341
< 0.1%
96671
< 0.1%
79311
< 0.1%
75741
< 0.1%
69071
< 0.1%
59661
< 0.1%
57051
< 0.1%
54341
< 0.1%
53851
< 0.1%
52881
< 0.1%

Interactions

2026-02-13T20:02:54.503342image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:50.939906image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:51.550495image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:52.107771image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:52.672841image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:53.286246image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:53.906060image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:54.590838image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:51.040024image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:51.636194image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:52.197622image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:52.806586image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:53.379642image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:54.007863image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:54.662209image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:51.120131image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:51.711904image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:52.271467image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:52.887775image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:53.463757image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:54.080187image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:54.745550image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:51.202483image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:51.791293image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:52.348526image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:52.963661image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:53.556697image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:54.160110image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:54.826774image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:51.290880image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:51.856061image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:52.425432image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:53.037543image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:53.640079image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:54.237232image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:54.914872image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:51.382870image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:51.948901image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:52.507058image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:53.128412image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:53.730100image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:54.322805image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:54.990675image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:51.466855image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:52.022650image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:52.594206image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:53.208202image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:53.816945image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2026-02-13T20:02:54.400704image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Correlations

2026-02-13T20:03:01.423777image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Aggregate ratingAverage Cost for twoCountry CodeCurrencyHas Online deliveryHas Table bookingIs delivering nowLatitudeLongitudePrice rangeRating colorRating textRestaurant IDVotes
Aggregate rating1.0000.2200.3930.1970.3050.2090.030-0.056-0.1390.3171.0001.000-0.2440.846
Average Cost for two0.2201.000-0.4010.3670.0000.0000.000-0.2190.1700.0580.0600.060-0.1820.346
Country Code0.393-0.4011.0000.9720.1620.0890.0000.094-0.3440.2280.2270.2270.0520.308
Currency0.1970.3670.9721.0000.1820.1300.0000.6850.7360.2370.2340.2340.4580.023
Has Online delivery0.3050.0000.1620.1821.0000.1000.0990.2070.2230.2740.3040.3040.1690.030
Has Table booking0.2090.0000.0890.1300.1001.0000.0100.1030.1290.5430.2080.2080.1410.134
Is delivering now0.0300.0000.0000.0000.0990.0101.0000.0000.0000.0370.0320.0320.0000.000
Latitude-0.056-0.2190.0940.6850.2070.1030.0001.0000.0290.2460.2460.246-0.115-0.018
Longitude-0.1390.170-0.3440.7360.2230.1290.0000.0291.0000.2140.2380.238-0.055-0.079
Price range0.3170.0580.2280.2370.2740.5430.0370.2460.2141.0000.3160.3160.2130.133
Rating color1.0000.0600.2270.2340.3040.2080.0320.2460.2380.3161.0001.0000.2670.150
Rating text1.0000.0600.2270.2340.3040.2080.0320.2460.2380.3161.0001.0000.2670.150
Restaurant ID-0.244-0.1820.0520.4580.1690.1410.000-0.115-0.0550.2130.2670.2671.000-0.476
Votes0.8460.3460.3080.0230.0300.1340.000-0.018-0.0790.1330.1500.150-0.4761.000

Missing values

2026-02-13T20:02:55.116920image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.
2026-02-13T20:02:55.366490image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Restaurant IDRestaurant NameCountry CodeCityAddressLocalityLocality VerboseLongitudeLatitudeCuisinesAverage Cost for twoCurrencyHas Table bookingHas Online deliveryIs delivering nowSwitch to order menuPrice rangeAggregate ratingRating colorRating textVotes
06317637Le Petit Souffle162Makati CityThird Floor, Century City Mall, Kalayaan Avenue, Poblacion, Makati CityCentury City Mall, Poblacion, Makati CityCentury City Mall, Poblacion, Makati City, Makati City121.02753514.565443French, Japanese, Desserts1100Botswana Pula(P)YesNoNoNo34.8Dark GreenExcellent314
16304287Izakaya Kikufuji162Makati CityLittle Tokyo, 2277 Chino Roces Avenue, Legaspi Village, Makati CityLittle Tokyo, Legaspi Village, Makati CityLittle Tokyo, Legaspi Village, Makati City, Makati City121.01410114.553708Japanese1200Botswana Pula(P)YesNoNoNo34.5Dark GreenExcellent591
26300002Heat - Edsa Shangri-La162Mandaluyong CityEdsa Shangri-La, 1 Garden Way, Ortigas, Mandaluyong CityEdsa Shangri-La, Ortigas, Mandaluyong CityEdsa Shangri-La, Ortigas, Mandaluyong City, Mandaluyong City121.05683114.581404Seafood, Asian, Filipino, Indian4000Botswana Pula(P)YesNoNoNo44.4GreenVery Good270
36318506Ooma162Mandaluyong CityThird Floor, Mega Fashion Hall, SM Megamall, Ortigas, Mandaluyong CitySM Megamall, Ortigas, Mandaluyong CitySM Megamall, Ortigas, Mandaluyong City, Mandaluyong City121.05647514.585318Japanese, Sushi1500Botswana Pula(P)NoNoNoNo44.9Dark GreenExcellent365
46314302Sambo Kojin162Mandaluyong CityThird Floor, Mega Atrium, SM Megamall, Ortigas, Mandaluyong CitySM Megamall, Ortigas, Mandaluyong CitySM Megamall, Ortigas, Mandaluyong City, Mandaluyong City121.05750814.584450Japanese, Korean1500Botswana Pula(P)YesNoNoNo44.8Dark GreenExcellent229
518189371Din Tai Fung162Mandaluyong CityGround Floor, Mega Fashion Hall, SM Megamall, Ortigas, Mandaluyong CitySM Megamall, Ortigas, Mandaluyong CitySM Megamall, Ortigas, Mandaluyong City, Mandaluyong City121.05631414.583764Chinese1000Botswana Pula(P)NoNoNoNo34.4GreenVery Good336
66300781Buffet 101162Pasay CityBuilding K, SM By The Bay, Sunset Boulevard, Mall of Asia Complex (MOA), Pasay CitySM by the Bay, Mall of Asia Complex, Pasay CitySM by the Bay, Mall of Asia Complex, Pasay City, Pasay City120.97966714.531333Asian, European2000Botswana Pula(P)YesNoNoNo44.0GreenVery Good520
76301290Vikings162Pasay CityBuilding B, By The Bay, Seaside Boulevard, Mall of Asia Complex (MOA), Pasay CitySM by the Bay, Mall of Asia Complex, Pasay CitySM by the Bay, Mall of Asia Complex, Pasay City, Pasay City120.97933314.540000Seafood, Filipino, Asian, European2000Botswana Pula(P)YesNoNoNo44.2GreenVery Good677
86300010Spiral - Sofitel Philippine Plaza Manila162Pasay CityPlaza Level, Sofitel Philippine Plaza Manila, CCP Complex, Pasay CitySofitel Philippine Plaza Manila, Pasay CitySofitel Philippine Plaza Manila, Pasay City, Pasay City120.98009014.552990European, Asian, Indian6000Botswana Pula(P)YesNoNoNo44.9Dark GreenExcellent621
96314987Locavore162Pasig CityBrixton Technology Center, 10 Brixton Street, Kapitolyo, Pasig CityKapitolyoKapitolyo, Pasig City121.05653214.572041Filipino1100Botswana Pula(P)YesNoNoNo34.8Dark GreenExcellent532
Restaurant IDRestaurant NameCountry CodeCityAddressLocalityLocality VerboseLongitudeLatitudeCuisinesAverage Cost for twoCurrencyHas Table bookingHas Online deliveryIs delivering nowSwitch to order menuPrice rangeAggregate ratingRating colorRating textVotes
95415905215Emirgan Sí_tiô208ÛÁstanbulEmirgan Mahallesi, SakÛ±p SabancÛ± Caddesi, No 46, SarÛ±yer, ÛÁstanbulEmirgí¢nEmirgí¢n, ÛÁstanbul29.05662041.104969Restaurant Cafe, Turkish, Desserts75Turkish Lira(TL)NoNoNoNo34.2GreenVery Good877
95425926979Leman Kí_ltí_r208ÛÁstanbulCaferaÛôa Mahallesi, Neôet í_mer Sokak, No 9/A, KadÛ±kí_y, ÛÁstanbulKadÛ±kí_y MerkezKadÛ±kí_y Merkez, ÛÁstanbul29.02280540.989705Restaurant Cafe80Turkish Lira(TL)NoNoNoNo33.7YellowGood506
95435916085Dem Karakí_y208ÛÁstanbulKemankeô Karamustafa Paôa Mahallesi, Hoca Tahsin Sokak, No 17, BeyoÛôlu, ÛÁstanbulKarakí_yKarakí_y, ÛÁstanbul28.97823741.024633Cafe35Turkish Lira(TL)NoNoNoNo24.5Dark GreenExcellent761
95445915547Karakí_y Gí_llí_oÛôlu208ÛÁstanbulKemankeô Karamustafa Paôa Mahallesi, RÛ±htÛ±m Caddesi, KatlÛ± Otopark AltÛ±, No 4, BeyoÛôlu, ÛÁstanbulKarakí_yKarakí_y, ÛÁstanbul28.97763641.022904Desserts, Bí_rek40Turkish Lira(TL)NoNoNoNo24.7Dark GreenExcellent1305
95455915054Baltazar208ÛÁstanbulKemankeô Karamustafa Paôa Mahallesi, KÛ±lÛ±í_ Ali Paôa Mescidi Sokak, No 12/A, BeyoÛôlu, ÛÁstanbulKarakí_yKarakí_y, ÛÁstanbul28.98110341.025785Burger, Izgara90Turkish Lira(TL)NoNoNoNo34.3GreenVery Good870
95465915730NamlÛ± Gurme208ÛÁstanbulKemankeô Karamustafa Paôa Mahallesi, RÛ±htÛ±m Caddesi, No 1/1, KatlÛ± Otopark AltÛ±, BeyoÛôlu, ÛÁstanbulKarakí_yKarakí_y, ÛÁstanbul28.97739241.022793Turkish80Turkish Lira(TL)NoNoNoNo34.1GreenVery Good788
95475908749Ceviz AÛôacÛ±208ÛÁstanbulKoôuyolu Mahallesi, Muhittin íìstí_ndaÛô Caddesi, No 85, KadÛ±kí_y, ÛÁstanbulKoôuyoluKoôuyolu, ÛÁstanbul29.04129741.009847World Cuisine, Patisserie, Cafe105Turkish Lira(TL)NoNoNoNo34.2GreenVery Good1034
95485915807Huqqa208ÛÁstanbulKuruí_eôme Mahallesi, Muallim Naci Caddesi, No 56, Beôiktaô, ÛÁstanbulKuruí_eômeKuruí_eôme, ÛÁstanbul29.03464041.055817Italian, World Cuisine170Turkish Lira(TL)NoNoNoNo43.7YellowGood661
95495916112Aôôk Kahve208ÛÁstanbulKuruí_eôme Mahallesi, Muallim Naci Caddesi, No 64/B, Beôiktaô, ÛÁstanbulKuruí_eômeKuruí_eôme, ÛÁstanbul29.03601941.057979Restaurant Cafe120Turkish Lira(TL)NoNoNoNo44.0GreenVery Good901
95505927402Walter's Coffee Roastery208ÛÁstanbulCafeaÛôa Mahallesi, BademaltÛ± Sokak, No 21/B, KadÛ±kí_y, ÛÁstanbulModaModa, ÛÁstanbul29.02601640.984776Cafe55Turkish Lira(TL)NoNoNoNo24.0GreenVery Good591